matlab-shipinfenxidianzishu

由matlab仿真的,超宽带信号中估计带宽程序(By matlab simulation, ultra-wideband signal bandwidth procedure estimated)

自适应滤波算法的应用，自适应信号对消的一种例子(The application of adaptive filtering algorithms, adaptive signal cancellation of a case)

matlab的细化谱代码。包含一个细化谱文件和一个应用文件。(Matlab refinement spectrum code. Contains a detailed spectrum of file and application files.)

利用高阶模糊函数算法，对线性调频信号传播过程中的非线性问题估计并校正(The use of higher-order ambiguity function algorithm for linear frequency modulated signal propagation in nonlinear estimation problem and correct)

利用MATlab进行混合溶液沸点的计算，里面包含的模型自己参照，值得学习和推荐。(Mixed solution using MATlab boiling point calculation, which contains its own reference model, it is worth learning and recommendations.)

fAST FOURIER EXAMPLE

matlab code for finding exon prediction in DNA strand

Color can provide an efficient visual feature for tracking nonrigid objects in real-time. However, the color of an object can vary over time dependent on the illumination, the visual angle and the camera parameters. To handle these appearance changes a color-based target model must be adapted during temporally stable image observations. This paper presents the integration of color distributions into particle filtering and shows how these distributions can be adapted over time. A particle filter tracks several hypotheses simultaneously and weights them according to their similarity to the target model. As similarity measure between two color distributions the popular Bhattacharyya coefficient is applied. In order to update the target model to slowly varying image conditions, frames where the object is occluded or too noisy must be discarded.

ekf滤波、pda关联滤波、卡尔曼滤波、最小二乘参数估计的仿真建模，以及matlab多项式的学习资料(ekf filtering, pda association filtering, Kalman filtering, least squares parameter estimation modeling and simulation, as well as learning materials matlab polynomial)

对一维语音信号进行分解和重构运算，最后比较原信号与生成信号的区别(On the one-dimensional speech signal decomposition and reconstruction operations, and finally compare the original signal and the difference between the signal generated)